随着现代睡眠监测需求的不断提高，单一传感器进行非接触式睡眠监测在精度和性能上均不能满足相关需求，研究更加全面、精准、高效的非接触式睡眠监测理论与关键技术已成为睡眠医学重要问题之一。本项目将开展基于多模态异质信息融合的非接触式睡眠监测理论与关键技术的研究，研究内容主要包括多模态睡眠生理信息感知机理研究、多模态睡眠异质特征提取和筛选、多模态睡眠信息融合方法、基于多模态异质信息融合的睡眠质量评估等。研究中将多模态信息融合和机器学习应用到非接触式睡眠监测技术中，充分发挥射频和声传感器的联合优势，深度挖掘多模态睡眠“隐性”信息，实现多模态睡眠异质信息的互补，提高非接触式睡眠监测的准确性和鲁棒性。本项目是对非接触式睡眠技术的进一步深化研究，将为解决非接触式睡眠监测问题探索新的方案。研究成果将为我国非接触式睡眠监测领域的发展提供重要的研究积累和技术支撑。

With the continuously improved requirements of modern sleep monitoring, non-contact sleep detection with single sensor cannot meet the requirements in both accuracy and performance. More comprehensive, precise and efficient theory and key technology for non-contact sleep monitoring have become one of the key issues in sleep medicine. The research on the theory and key technology of non-contact sleep monitoring based on multi-modal heterogeneous information fusion will be carried out in this project. This research mainly include the research on the sensing mechanism of multi-modal sleep physiological information, the extraction and screening of multi-modal sleep heterogeneity features, multi-modal sleep information fusion method, sleep quality assessment based on multi-modal heterogeneous information fusion and so on. In this research, multi-modal information fusion and machine learning are applied to the non-contact sleep monitoring technology. The advantages of combing the radio frequency and acoustic sensors are fully exploited. The "implicit" information of multi-modal sleep is deeply tapped. The multi-modal heterogeneous sleep information are complemented. The accuracy and robustness of non-contact sleep monitoring are improved. The project is the further study of non-contact sleep technology. It will explore new solutions to solve the problem of non-contact sleep monitoring. The research results will provide important research accumulation and technical support for the development of non-contact sleep monitoring in our country.